DOCSLIB.ORG

Next-Generation Sequencing Expanded NGS Gene List

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Next-Generation Sequencing Expanded NGS Gene List Next-Generation Sequencing Expanded NGS Gene List Mutations (DNA) ABI1 BRD4 CRLF2 FOXO4 HOXC11 KLF4 MUC1 PAK3 RHOH TAL2 ABL1 BTG1 DDB2 FSTL3 HOXC13 KLK2 MUTYH PATZ1 RNF213 TBL1XR1 ACKR3 BTK DDIT3 GATA1 HOXD11 LASP1 MYCL (MYCL1) PAX8 RPL10 TCEA1 AKT1 C15orf65 DNM2 GATA2 HOXD13 LMO1 NBN PDE4DIP SEPT5 TCL1A ® AMER1 (FAM123B) CBLC DNMT3A GNA11 HRAS LMO2 NDRG1 PHF6 SEPT6 TERT Tumor Profiling Services from Caris Molecular Intelligence AR CD79B EIF4A2 GPC3 IKBKE MAFB NKX2-1 PHOX2B SFPQ TFE3 ARAF CDH1 ELF4 HEY1 INHBA MAX NONO PIK3CG SLC45A3 TFPT ATP2B3 CDK12 ELN HIST1H3B IRS2 MECOM NOTCH1 PLAG1 SMARCA4 THRAP3 ATRX CDKN2B ERCC1 HIST1H4I JUN MED12 NRAS PMS1 SOCS1 TLX3 BCL11B CDKN2C ETV4 HLF KAT6A (MYST3) MKL1 NUMA1 POU5F1 SOX2 TMPRSS2 BCL2 CEBPA FAM46C HMGN2P46 KAT6B MLLT11 NUTM2B PPP2R1A SPOP UBR5 Next-Generation BCL2L2 CHCHD7 FANCF HNF1A KCNJ5 MN1 OLIG2 PRF1 SRC VHL Sequencing BCOR CNOT3 FEV HOXA11 KDM5C MPL OMD PRKDC SSX1 WAS Multi-platform, solid tumor BCORL1 COL1A1 FOXL2 HOXA13 KDM6A MSN P2RY8 RAD21 STAG2 ZBTB16 Next-Generation Sequencing for BRD3 COX6C FOXO3 HOXA9 KDSR MTCP1 PAFAH1B2 RECQL4 TAL1 ZRSR2 biomarker analysis for therapeutic decision support additional biomarker analysis Mutations and Copy Number Variations (DNA) ABL2 BRCA21 COPB1 ESR1 FUS KIT MYB PER1 RUNX1 TFG ACSL3 BRIP1 CREB1 ETV1 GAS7 KLHL6 MYC PICALM RUNX1T1 TFRC Chemotherapy 4 – ACSL6 BUB1B CREB3L1 ETV5 GATA3 KMT2A (MLL) MYCN PIK3CA SBDS TGFBR2 AFF1 C11orf30 (EMSY) CREB3L2 ETV6 GID4 (C17orf39) KMT2C (MLL3) MYD88 PIK3R1 SDC4 TLX1 Immunotherapy 4 – AFF3 C2orf44 CREBBP EWSR1 GMPS KMT2D (MLL2) MYH11 PIK3R2 SDHAF2 TNFAIP3 AFF4 CACNA1D CRKL EXT1 GNA13 KRAS MYH9 PIM1 SDHB TNFRSF14 Targeted Therapy 4 4 AKAP9 CALR CRTC1 EXT2 GNAQ KTN1 NACA PML SDHC TNFRSF17 AKT2 CAMTA1 CRTC3 EZH2 GNAS LCK NCKIPSD PMS2 SDHD TOP1 Protein Expression via IHC 4 – AKT3 CANT1 CSF1R EZR GOLGA5 LCP1 NCOA1 POLE SEPT9 TP53 ALDH2 CARD11 CSF3R FANCA GOPC LGR5 NCOA2 POT1 SET TPM3 DNA Analysis via Pyro Sequencing 4 – ALK CARS CTCF FANCC GPHN LHFP NCOA4 POU2AF1 SETBP1 TPM4 DNA/RNA Analysis APC CASC5 CTLA4 FANCD2 GPR124 LIFR NF1 PPARG SETD2 TPR 4 – ARFRP1 CASP8 CTNNA1 FANCE GRIN2A LPP NF2 PRCC SF3B1 TRAF7 via Fragment Analysis ARHGAP26 CBFA2T3 CTNNB1 FANCG GSK3B LRIG3 NFE2L2 PRDM1 SH2B3 TRIM26 Molecular Analysis ARHGEF12 CBFB CYLD FANCL H3F3A LRP1B NFIB PRDM16 SH3GL1 TRIM27 592 Genes 592 Genes ARID1A CBL CYP2D6 FAS H3F3B LYL1 NFKB2 PRKAR1A SLC34A2 TRIM33 via Next-Generation Sequencing ARID2 CBLB DAXX FBXO11 HERPUD1 MAF NFKBIA PRRX1 SMAD2 TRIP11 ARNT CCDC6 DDR2 FBXW7 HGF MALT1 NIN PSIP1 SMAD4 TRRAP Clinical Trial Opportunities 4 4 ASPSCR1 CCNB1IP1 DDX10 FCRL4 HIP1 MAML2 NOTCH2 PTCH1 SMARCB1 TSC1 ASXL1 CCND1 DDX5 FGF10 HMGA1 MAP2K1 NPM1 PTEN SMARCE1 TSC2 ATF1 CCND2 DDX6 FGF14 HMGA2 MAP2K2 NR4A3 PTPN11 SMO TSHR ATIC CCND3 DEK FGF19 HNRNPA2B1 MAP2K4 NSD1 PTPRC SNX29 TTL ATM CCNE1 DICER1 FGF23 HOOK3 MAP3K1 NT5C2 RABEP1 SOX10 U2AF1 Technical Specifications ATP1A1 CD274 (PDL1) DOT1L FGF3 HSP90AA1 MCL1 NTRK1 RAC1 SPECC1 USP6 ATR CD74 EBF1 FGF4 HSP90AB1 MDM2 NTRK2 RAD50 SPEN VEGFA AURKA CD79A ECT2L FGF6 IDH1 MDM4 NTRK3 RAD51 SRGAP3 VEGFB Sufficient tumor must be present to complete all analysis. If you have any questions, please contact Client Services at (888) 979-8669. AURKB CDC73 EGFR FGFR1 IDH2 MDS2 NUP214 RAD51B SRSF2 VTI1A AXIN1 CDH11 ELK4 FGFR1OP IGF1R MEF2B NUP93 RAF1 SRSF3 WHSC1 Technical Information IHC CISH FISH AXL CDK4 ELL FGFR2 IKZF1 MEN1 NUP98 RALGDS SS18 WHSC1L1 BAP1 CDK6 EML4 FGFR3 IL2 MET (cMET) NUTM1 RANBP17 SS18L1 WIF1 1 unstained slide at 4μm thickness from FFPE 1 unstained slide at 4μm thickness from FFPE 2 unstained slides at 4μm thickness from FFPE Sample Requirements BARD1 CDK8 EP300 FGFR4 IL21R MITF PALB2 RAP1GDS1 STAT3 WISP3 block, with evaluable tumor present, per block, with at least 20-100 evaluable tumor block, with at least 100 evaluable cells present (see requsition for full details) BCL10 CDKN1B EPHA3 FH IL6ST MLF1 PAX3 RARA STAT4 WRN IHC test cells present, per CISH test and 10% tumor, per FISH test BCL11A CDKN2A EPHA5 FHIT IL7R MLH1 PAX5 RB1 STAT5B WT1 BCL2L11 CDX2 EPHB1 FIP1L1 IRF4 MLLT1 PAX7 RBM15 STIL WWTR1 Sensitivity/Specificity >95% >95% >95% BCL3 CHEK1 EPS15 FLCN ITK MLLT10 PBRM1 REL STK11 XPA BCL6 CHEK2 ERBB2 (HER2) FLI1 JAK1 MLLT3 PBX1 RET SUFU XPC BCL7A CHIC2 ERBB3 (HER3) FLT1 JAK2 MLLT4 PCM1 RICTOR SUZ12 XPO1 Next-Generation Sequencing BCL9 CHN1 ERBB4 (HER4) FLT3 JAK3 MLLT6 PCSK7 RMI2 SYK YWHAE Technical Information BCR CIC ERC1 FLT4 JAZF1 MNX1 PDCD1 (PD1) RNF43 TAF15 ZMYM2 Mutations and Copy Number Variations (DNA) Fusions (RNA) BIRC3 CIITA ERCC2 FNBP1 KDM5A MRE11A PDCD1LG2 (PDL2) ROS1 TCF12 ZNF217 BLM CLP1 ERCC3 FOXA1 KDR (VEGFR2) MSH2 PDGFB RPL22 TCF3 ZNF331 FFPE block or 15 unstained slides with a minimum of 20% FFPE block or 2-5 unstained slides with a minimum of 20% Sample Requirements BMPR1A CLTC ERCC4 FOXO1 KEAP1 MSH6 PDGFRA RPL5 TCF7L2 ZNF384 malignant origin. Needle biopsy is also acceptable (4-6 cores). malignant origin. Needle biopsy is also acceptable (4-6 cores). BRAF CLTCL1 ERCC5 FOXP1 KIAA1549 MSI2 PDGFRB RPN1 TET1 ZNF521 BRCA11 CNBP ERG FUBP1 KIF5B MTOR PDK1 RPTOR TET2 ZNF703 Tumor Enrichment Microdissection performed on all cases resulting in ~25% increase in tumor nuclei and enhances detection of minor clonal variants CNTRL TFEB Gene Fusions (RNA) Variant Transcripts (RNA) Amount of DNA Required 200ng input (50ng) MET Exon 14 ALK BRAF NTRK1 NTRK2 NTRK3 RET ROS1 RSPO3 EGFR vIII Skipping PPV >99% >98% > 99% for base substitutions at ≥ 5% mutant allele frequency; 1 May not be available for Medicare patients. Medicare reimburses BRCA1-2 for breast and ovarian cases only. Sensitivity > 99% for indels at ≥ 5% mutant allele frequency; >91% Next-Generation Sequencing may not be available in New York State. For testing available in New York, please view >95% for copy number variations (amplifications ≥ 8 copies) the online New York Profile Menu (www.CarisMolecularIntelligence.com/solid_tumors-NY). Average Depth of Coverage (DNA) >750X >30,000 Unique RNA Fragments Average Depth/Count (RNA) To order or learn more, visit www.CarisMolecularIntelligence.com. Number of Genes 592 genes 10 genes US: 888.979.8669 | [email protected] Caris Molecular Intelligence is a trademark of Caris Life Sciences. Intl: 00 41 21 533 53 00 | [email protected] © 2016 Caris Life Sciences. All rights reserved. TN0276 v5 December 14, 2016 Caris Molecular Intelligence®Associations List Biomarker Analysis by Tumor Type The list below details the biomarkers assessed, technology platforms utilized and associated therapies or clinical trials. The information below details the biomarkers analyzed by technology for the tumor type submitted. Before ordering Biomarkers and therapy associations may vary by the tumor type submitted. The current and definitive list menu can be testing services, please refer to the profile menu online (www.CarisMolecularIntelligence.com/profilemenu) to view the found online at www.CarisMolecularIntelligence.com/profilemenu. most up-to-date listing of biomarkers that will be performed. Tests may vary if insufficient tumor samples are submitted. Individual assay results are always included with the final report. MI Profile™ Agent Biomarker Platform Agent Biomarker Platform Next-Generation Sequencing (NGS) EGFR NGS Mutation ER Tumor Type Immunohistochemistry (IHC) (see reverse for gene list) Other afatinib (assoc. in Breast only) IHC (assoc. in NSCLC only) ERBB2 (Her2) NGS Mutation everolimus, temsirolimus PIK3CA NGS Mutation ERCC1, PD-L1, RRM1, TOP2A, TRKA/B/C (NTRK), (excluding CRC) Bladder Mutation, CNV Analysis (DNA) afatinib + cetuximab EGFR T790M NGS Mutation TS, TUBB3 (combination assoc. in NSCLC only) exemestane + everolimus, fulvestrant, ER IHC IHC; NGS Fusion Analysis AR, ER, ERCC1, Her2/Neu, PD-L1, PR, PTEN, TOPO1, TOP2A (Chromogenic in situ alectinib, ceritinib ALK pabociclib combination therapy ESR1 NGS Mutation Breast Mutation, CNV Analysis (DNA) (RNA) TRKA/B/C (NTRK), TS Hybridization) gemcitabine RRM1 IHC aspirin PIK3CA NGS Mutation Cancer of Unknown ERCC1, PD-L1, RRM1, TOPO1, TRKA/B/C (NTRK), (assoc. in CRC only) Mutation, CNV Analysis (DNA) AR IHC Primary TS, TUBB3 atezolizumab PD-L1 IHC (assoc. in NSCLC only) ER, ERCC1, PD-L1, PR, RRM1, TOP2A, TOPO1, hormone therapies3 ER IHC Cervix Mutation, CNV Analysis (DNA) cabozantinib RET NGS Fusion Analysis (RNA) TRKA/B/C (NTRK), TS, TUBB3 capecitabine, fluorouracil, pemetrexed TS IHC PR IHC Cholangiocarcinoma/ ERCC1, Her2/Neu, PD-L1, RRM1, TOPO1, Mutation, CNV Analysis (DNA) ATM NGS Mutation cKIT NGS Mutation Hepatobiliary TRKA/B/C (NTRK), TS, TUBB3 BRCA11 NGS Mutation imatinib ERCC1, MLH1, MSH2, MSH6, PD-L1, PMS2, PTEN, carboplatin, cisplatin, oxaliplatin PDGFRA NGS Mutation Colorectal Mutation, CNV Analysis (DNA) MSI1 (Fragment Analysis) BRCA21 NGS Mutation TOPO1, TRKA/B/C (NTRK), TS irinotecan ER, ERCC1, MLH1, MSH2, MSH6, PMS2, PR, PD-L1, PTEN, ERCC1 IHC TOPO1 IHC Endometrial Mutation, CNV Analysis (DNA) MSI1 (Fragment Analysis) topotecan RRM1, TOP2A, TOPO1, TRKA/B/C (NTRK), TS, TUBB3 BRAF NGS Mutation (excluding Breast, CRC, NSCLC) ERCC1, Her2/Neu, PD-L1, TOP2A, TOPO1, KRAS NGS Mutation Gastric Mutation, CNV Analysis (DNA) lapatinib, pertuzumab, T-DM1 Her2/Neu NGS CNV (DNA) TRKA/B/C (NTRK), TS, TUBB3 cetuximab, panitumumab2 NRAS NGS Mutation 1 (assoc. in CRC only) BRCA1 PIK3CA NGS Mutation mitomycin-c NGS Mutation GIST PD-L1, PTEN, TRKA/B/C (NTRK) Mutation, CNV Analysis (DNA) BRCA21 PTEN IHC Mutation, CNV (DNA); MGMT Methylation PD-L1 IHC Glioma ERCC1, PD-L1, TOPO1 cetuximab EGFR NGS CNV nivolumab, pembrolizumab Fusion Analysis (RNA) (Pyrosequencing) (assoc. in Bladder, Kidney, Melanoma, NSCLC only) MSI IHC; NGS Mutation (DNA) & (pembrolizumab only) FA ALK Fusion Analysis (RNA) Head & Neck ERCC1, PD-L1, RRM1, TRKA/B/C (NTRK), TS, TUBB3 Mutation, CNV Analysis (DNA) ATM crizotinib cMET NGS Mutation, CNV (DNA) (assoc. in Prostate only) olaparib BRCA11 NGS Mutation Kidney ERCC1, PD-L1, RRM1, TOP2A, TRKA/B/C (NTRK), TUBB3 Mutation, CNV Analysis (DNA) ROS1 NGS Fusion Analysis (RNA) BRCA21 dabrafenib, vemurafenib2 BRAF NGS Mutation Melanoma ERCC1, MGMT, PD-L1, TRKA/B/C (NTRK), TUBB3 Mutation, CNV Analysis (DNA) osimertinib MGMT IHC EGFR T790M NGS Mutation (assoc.
Load more

Recommended publications
  • KAT6A Syndrome: Genotype-Phenotype Correlation in 76 Patients with Pathogenic KAT6A Variants
    KAT6A Syndrome: genotype-phenotype correlation in 76 patients with pathogenic KAT6A variants. Item Type Article Authors Kennedy, Joanna;Goudie, David;Blair, Edward;Chandler, Kate;Joss, Shelagh;McKay, Victoria;Green, Andrew;Armstrong, Ruth;Lees, Melissa;Kamien, Benjamin;Hopper, Bruce;Tan, Tiong Yang;Yap, Patrick;Stark, Zornitza;Okamoto, Nobuhiko;Miyake, Noriko;Matsumoto, Naomichi;Macnamara, Ellen;Murphy, Jennifer L;McCormick, Elizabeth;Hakonarson, Hakon;Falk, Marni J;Li, Dong;Blackburn, Patrick;Klee, Eric;Babovic- Vuksanovic, Dusica;Schelley, Susan;Hudgins, Louanne;Kant, Sarina;Isidor, Bertrand;Cogne, Benjamin;Bradbury, Kimberley;Williams, Mark;Patel, Chirag;Heussler, Helen;Duff- Farrier, Celia;Lakeman, Phillis;Scurr, Ingrid;Kini, Usha;Elting, Mariet;Reijnders, Margot;Schuurs-Hoeijmakers, Janneke;Wafik, Mohamed;Blomhoff, Anne;Ruivenkamp, Claudia A L;Nibbeling, Esther;Dingemans, Alexander J M;Douine, Emilie D;Nelson, Stanley F;Arboleda, Valerie A;Newbury-Ecob, Ruth DOI 10.1038/s41436-018-0259-2 Journal Genetics in medicine : official journal of the American College of Medical Genetics Download date 30/09/2021 21:53:13 Link to Item http://hdl.handle.net/10147/627191 Find this and similar works at - http://www.lenus.ie/hse HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Genet Med Manuscript Author . Author manuscript; Manuscript Author available in PMC 2019 October 01. Published in final edited form as: Genet Med. 2019 April ; 21(4): 850–860. doi:10.1038/s41436-018-0259-2. KAT6A Syndrome: Genotype-phenotype correlation in 76 patients with pathogenic KAT6A variants A full list of authors and affiliations appears at the end of the article. Abstract Purpose: Mutations in KAT6A have recently been identified as a cause of syndromic developmental delay.
    [Show full text]
  • ONCOPANEL (Popv3)
    ONCOPANEL (POPv3) TEST INFORMATION BACKGROUND: Somatic genetic alterations in oncogenes and tumor-suppressor genes contribute to the pathogenesis and evolution of human cancers. These alterations can provide prognostic and predictive information and stratify cancers for targeted therapeutic information. We classify these alterations into five tiers using the following guidelines: Tier 1: The alteration has well-established published evidence confirming clinical utility in this tumor type, in at least one of the following contexts: predicting response to treatment with an FDA-approved therapy; assessing prognosis; establishing a definitive diagnosis; or conferring an inherited increased risk of cancer to this patient and family. Tier 2: The alteration may have clinical utility in at least one of the following contexts: selection of an investigational therapy in clinical trials for this cancer type; limited evidence of prognostic association; supportive of a specific diagnosis; proven association of response to treatment with an FDA-approved therapy in a different type of cancer; or similar to a different mutation with a proven association with response to treatment with an FDA-approved therapyin this type of cancer. Tier 3: The alteration is of uncertain clinical utility, but may have a role as suggested by at least one of the following: demonstration of association with response to treatment in this cancer type in preclinical studies (e.g., in vitro studies or animal models); alteration in a biochemical pathway that has other known, therapeutically-targetable alterations; alteration in a highly conserved region of the protein predicted, in silico, to alter protein function; or selection of an investigational therapy for a different cancer type.
    [Show full text]
  • Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
    Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897
    [Show full text]
  • The Rac Gtpase in Cancer: from Old Concepts to New Paradigms Marcelo G
    Published OnlineFirst August 14, 2017; DOI: 10.1158/0008-5472.CAN-17-1456 Cancer Review Research The Rac GTPase in Cancer: From Old Concepts to New Paradigms Marcelo G. Kazanietz1 and Maria J. Caloca2 Abstract Rho family GTPases are critical regulators of cellular func- mislocalization of Rac signaling components. The unexpected tions that play important roles in cancer progression. Aberrant pro-oncogenic functions of Rac GTPase-activating proteins also activity of Rho small G-proteins, particularly Rac1 and their challenged the dogma that these negative Rac regulators solely regulators, is a hallmark of cancer and contributes to the act as tumor suppressors. The potential contribution of Rac tumorigenic and metastatic phenotypes of cancer cells. This hyperactivation to resistance to anticancer agents, including review examines the multiple mechanisms leading to Rac1 targeted therapies, as well as to the suppression of antitumor hyperactivation, particularly focusing on emerging paradigms immune response, highlights the critical need to develop ther- that involve gain-of-function mutations in Rac and guanine apeutic strategies to target the Rac pathway in a clinical setting. nucleotide exchange factors, defects in Rac1 degradation, and Cancer Res; 77(20); 5445–51. Ó2017 AACR. Introduction directed toward targeting Rho-regulated pathways for battling cancer. Exactly 25 years ago, two seminal papers by Alan Hall and Nearly all Rho GTPases act as molecular switches that cycle colleagues illuminated us with one of the most influential dis- between GDP-bound (inactive) and GTP-bound (active) forms. coveries in cancer signaling: the association of Ras-related small Activation is promoted by guanine nucleotide exchange factors GTPases of the Rho family with actin cytoskeleton reorganization (GEF) responsible for GDP dissociation, a process that normally (1, 2).
    [Show full text]
  • The New Therapeutic Strategies in Pediatric T-Cell Acute Lymphoblastic Leukemia
    International Journal of Molecular Sciences Review The New Therapeutic Strategies in Pediatric T-Cell Acute Lymphoblastic Leukemia Marta Weronika Lato 1 , Anna Przysucha 1, Sylwia Grosman 1, Joanna Zawitkowska 2 and Monika Lejman 3,* 1 Student Scientific Society, Laboratory of Genetic Diagnostics, Medical University of Lublin, 20-093 Lublin, Poland; [email protected] (M.W.L.); [email protected] (A.P.); [email protected] (S.G.) 2 Department of Pediatric Hematology, Oncology and Transplantology, Medical University of Lublin, 20-093 Lublin, Poland; [email protected] 3 Laboratory of Genetic Diagnostics, Medical University of Lublin, 20-093 Lublin, Poland * Correspondence: [email protected] Abstract: Childhood acute lymphoblastic leukemia is a genetically heterogeneous cancer that ac- counts for 10–15% of T-cell acute lymphoblastic leukemia (T-ALL) cases. The T-ALL event-free survival rate (EFS) is 85%. The evaluation of structural and numerical chromosomal changes is important for a comprehensive biological characterization of T-ALL, but there are currently no ge- netic prognostic markers. Despite chemotherapy regimens, steroids, and allogeneic transplantation, relapse is the main problem in children with T-ALL. Due to the development of high-throughput molecular methods, the ability to define subgroups of T-ALL has significantly improved in the last few years. The profiling of the gene expression of T-ALL has led to the identification of T-ALL subgroups, and it is important in determining prognostic factors and choosing an appropriate treatment. Novel therapies targeting molecular aberrations offer promise in achieving better first remission with the Citation: Lato, M.W.; Przysucha, A.; hope of preventing relapse.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • A GTP-State Specific Cyclic Peptide Inhibitor of the Gtpase Gαs
    bioRxiv preprint doi: https://doi.org/10.1101/2020.04.25.054080; this version posted April 27, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. A GTP-state specific cyclic peptide inhibitor of the GTPase Gαs Shizhong A. Dai1,2†, Qi Hu1,2†, Rong Gao3†, Andre Lazar1,4†, Ziyang Zhang1,2, Mark von Zastrow1,4, Hiroaki Suga3*, Kevan M. Shokat1,2* 5 1Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, 94158, USA 2Howard Hughes Medical Institute 3Department of Chemistry, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan 10 4Department of Psychiatry, University of California, San Francisco, San Francisco, CA, 94158, USA *Correspondence to: [email protected], [email protected] †These authors contributed equally. 15 20 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.04.25.054080; this version posted April 27, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract: The G protein-coupled receptor (GPCR) cascade leading to production of the second messenger cAMP is replete with pharmacologically targetable receptors and enzymes with the exception of the stimulatory G protein α subunit, Gαs.
    [Show full text]
  • FANCL Sirna (H): Sc-45661
    SAN TA C RUZ BI OTEC HNOL OG Y, INC . FANCL siRNA (h): sc-45661 BACKGROUND STORAGE AND RESUSPENSION Defects in FANCL are a cause of Fanconi anemia. Fanconi anemia (FA) is an Store lyophilized siRNA duplex at -20° C with desiccant. Stable for at least autosomal recessive disorder characterized by bone marrow failure, birth one year from the date of shipment. Once resuspended, store at -20° C, defects and chromosomal instability. At the cellular level, FA is characterized avoid contact with RNAses and repeated freeze thaw cycles. by spontaneous chromosomal breakage and a unique hypersensitivity to DNA Resuspend lyophilized siRNA duplex in 330 µl of the RNAse-free water cross-linking agents. At least 8 complementation groups have been identified pro vided. Resuspension of the siRNA duplex in 330 µl of RNAse-free water and 6 FA genes (for subtypes A, C, D2, E, F and G) have been cloned. Phospho- makes a 10 µM solution in a 10 µM Tris-HCl, pH 8.0, 20 mM NaCl, 1 mM rylation of FANC (Fanconi anemia complementation group) proteins is thought EDTA buffered solution. to be important for the function of the FA pathway. FA proteins cooperate in a common pathway, culminating in the monoubiquitination of FANCD2 protein APPLICATIONS and colocalization of FANCD2 and BRCA1 proteins in nuclear foci. FANCL is a ligase protein mediating the ubiquitination of FANCD2, a key step in the FANCL shRNA (h) Lentiviral Particles is recommended for the inhibition of DNA damage pathway. FANCL may be required for proper primordial germ cell FANCL expression in human cells.
    [Show full text]
  • Further Insights Into the Regulation of the Fanconi Anemia FANCD2 Protein
    University of Rhode Island DigitalCommons@URI Open Access Dissertations 2015 Further Insights Into the Regulation of the Fanconi Anemia FANCD2 Protein Rebecca Anne Boisvert University of Rhode Island, [email protected] Follow this and additional works at: https://digitalcommons.uri.edu/oa_diss Recommended Citation Boisvert, Rebecca Anne, "Further Insights Into the Regulation of the Fanconi Anemia FANCD2 Protein" (2015). Open Access Dissertations. Paper 397. https://digitalcommons.uri.edu/oa_diss/397 This Dissertation is brought to you for free and open access by DigitalCommons@URI. It has been accepted for inclusion in Open Access Dissertations by an authorized administrator of DigitalCommons@URI. For more information, please contact [email protected]. FURTHER INSIGHTS INTO THE REGULATION OF THE FANCONI ANEMIA FANCD2 PROTEIN BY REBECCA ANNE BOISVERT A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN CELL AND MOLECULAR BIOLOGY UNIVERSITY OF RHODE ISLAND 2015 DOCTOR OF PHILOSOPHY DISSERTATION OF REBECCA ANNE BOISVERT APPROVED: Dissertation Committee: Major Professor Niall Howlett Paul Cohen Becky Sartini Nasser H. Zawia DEAN OF THE GRADUATE SCHOOL UNIVERSITY OF RHODE ISLAND 2015 ABSTRACT Fanconi anemia (FA) is a rare autosomal and X-linked recessive disorder, characterized by congenital abnormalities, pediatric bone marrow failure and cancer susceptibility. FA is caused by biallelic mutations in any one of 16 genes. The FA proteins function cooperatively in the FA-BRCA pathway to repair DNA interstrand crosslinks (ICLs). The monoubiquitination of FANCD2 and FANCI is a central step in the activation of the FA-BRCA pathway and is required for targeting these proteins to chromatin.
    [Show full text]
  • Clinical Utility of Recently Identified Diagnostic, Prognostic, And
    Modern Pathology (2017) 30, 1338–1366 1338 © 2017 USCAP, Inc All rights reserved 0893-3952/17 $32.00 Clinical utility of recently identified diagnostic, prognostic, and predictive molecular biomarkers in mature B-cell neoplasms Arantza Onaindia1, L Jeffrey Medeiros2 and Keyur P Patel2 1Instituto de Investigacion Marques de Valdecilla (IDIVAL)/Hospital Universitario Marques de Valdecilla, Santander, Spain and 2Department of Hematopathology, MD Anderson Cancer Center, Houston, TX, USA Genomic profiling studies have provided new insights into the pathogenesis of mature B-cell neoplasms and have identified markers with prognostic impact. Recurrent mutations in tumor-suppressor genes (TP53, BIRC3, ATM), and common signaling pathways, such as the B-cell receptor (CD79A, CD79B, CARD11, TCF3, ID3), Toll- like receptor (MYD88), NOTCH (NOTCH1/2), nuclear factor-κB, and mitogen activated kinase signaling, have been identified in B-cell neoplasms. Chronic lymphocytic leukemia/small lymphocytic lymphoma, diffuse large B-cell lymphoma, follicular lymphoma, mantle cell lymphoma, Burkitt lymphoma, Waldenström macroglobulinemia, hairy cell leukemia, and marginal zone lymphomas of splenic, nodal, and extranodal types represent examples of B-cell neoplasms in which novel molecular biomarkers have been discovered in recent years. In addition, ongoing retrospective correlative and prospective outcome studies have resulted in an enhanced understanding of the clinical utility of novel biomarkers. This progress is reflected in the 2016 update of the World Health Organization classification of lymphoid neoplasms, which lists as many as 41 mature B-cell neoplasms (including provisional categories). Consequently, molecular genetic studies are increasingly being applied for the clinical workup of many of these neoplasms. In this review, we focus on the diagnostic, prognostic, and/or therapeutic utility of molecular biomarkers in mature B-cell neoplasms.
    [Show full text]
  • Benefits of Cancerplex
    CancerPlexSM is a comprehensive genetic assessment of a patient’s tumor that guides oncologists towards effective treatment options. What is CancerPlex? CancerPlex is a next generation DNA sequencing test for solid SM tumors. The specific coding regions of over 400 known cancer Potential outcomes from CancerPlex genes are simultaneously determined using a small amount of Identification of variants associated with response or resis- DNA extracted from tumor samples, including formalin-fixed, tance to an FDA-approved therapy for the patient’s disease. paraffin-embedded (FFPE) tissue and cell blocks from fine-needle aspirates or effusions. This analysis is performed in a single assay, Identification of variants associated with response or resis- simplifying and streamlining the test ordering process, and eliminat- tance to a therapy associated with another clinical indication. ing time consuming serial testing. Clinically actionable information unique to each patient’s tumor is consolidated into a simple report. Identification of variants associated with a therapy(s) in CancerPlex reveals missense changes, insertions and deletions, clinical development. and previously described rearrangements of ALK, RET, and ROS. Benefits of CancerPlex: CancerPlex genes were selected because of their importance in tumor The average turn-around-time for CancerPlex is under 10 biology. Analyzing more genes increases the chance of discovering business days, dramatically shortening the waiting period for actionable findings that lead to more choices for treatment. Our initial the start of treatment. results indicate that CancerPlex analysis identifies actionable findings up to 20% more frequently than previously published studies. CancerPlex ordering is simple: KEW provides all necessary shipping materials, can facilitate tissue retrieval and return with Since knowledge of tumor biology changes rapidly, CancerPlex pathologists, and manages 3rd party payment for the test.
    [Show full text]
  • Supplementary Tables
    Supp Table 1. Patient characteristics of samples used for colony assays, xenografts and intracellular colony assays Sr.No Age Sex Diagnosis Blast% Cytogenetics Mutations (IPSS) (AF%) Patient samples used for colony assays 1. 68 F Low risk 1% N/A None MDS 2. 78 M RAEB-1 7% N/A DNMT3A 3. 66 F High risk 12.2% 5q-,7q-,+11, DNMT3A MDS 20q- (28%) TP53 (58%) 4. 61 M High risk 6.2% Monosomy 7 ASXL1 (36%) MDS EZH2 (77%) RUNX1(18%) 5. 63 M Low risk Normal ETV6 (34%), MDS KRAS(15%), RUNX1 (40%), SRSF2 (43%), ZRSR2 (86%) 6. 62 F RAEB-2 Del 5q TP53 (7%) 7. 76 F t-MDS <1% Normal TET2(10%) 8. 80 M Low risk 5% Normal SF3B1(21%) MDS TET2(8%) ZRZR2(62%) 9. 74 F MPN 5% JAK2V617F+ 10. 76 M Low risk <1% Deletion Y None MDS 11. 84 M Low risk N/A N/A N/A MDS 12. 86 M Int-2 MDS 4-8% Normal U2AF1 (43%) blasts CBL (15%) 13. 64 M low risk 1-3% 20q deletion ASXL1 (17%) MDS SETBP1(17%) U2AF1(15%) 14. 81 F Low risk <1% Normal None MDS Patient samples used for PDX 15. 87 F Int-2 risk 1.2% Complex SETBP1 (38%) MDS cytogenetics, del 7, dup 11, del 13q 16. 59 F High-risk 7-10% Complex NRAS (12%), MDS cytogenetics RUNX1 (20%), (-5q31, -7q31, SRSF2 (22%), trisomy 8, del STAG2 (17%) 11q23 17. 79 F Int-2 risk 5-8% None MDS 18. 67 M MPN 6.6% Normal CALR (51%) IDH1(47%) PDGFRB (47%) Patient samples used for intracellular ASO uptake 19.
    [Show full text]